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Autonomous, ModelBased Diagnosis Agents defines and describes the implementation of an architecture for autonomous, modelbased diagnosis agents. It does this by developing a logic programming approach for modelbased diagnosis and introducing strategies to deal with more complex diagnosis problems, and then embedding the diagnosis framework into the agent architecture of vivid agents.Autonomous, ModelBased Diagnosis Agents surveys extended logic programming and shows how this expressive language is used to model diagnosis problems stemming from applications such as digital circuits, traffic control, integrity checking of a chemical database, alarmcorrelation in cellular phone networks, diagnosis of an automatic mirror furnace, and diagnosis of communication protocols. The book reviews a bottomup algorithm to remove contradiction from extended logic programs and substantially improves it by topdown evaluation of extended logic programs. Both algorithms are evaluated in the circuit domain including some of the ISCAS85 benchmark circuits.This comprehensive indepth study of concepts, architectures, and implementation of autonomous, modelbased diagnosis agents will be of great value for researchers, engineers, and graduate students with a background in artificial intelligence. For practitioners, it provides three main contributions: first, it provides many examples from diverse areas such as alarm correlation in phone networks to inconsistency checking in databases; second, it describes an architecture to develop agents; and third, it describes a sophisticated and declarative implementation of the concepts and architectures introduced.
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